Desertification is defined as land degradation in arid, semiarid, and dry sub-humid regions, and it is caused primarily by human activities and climate change. The semiarid region of Northeast (NE) Brazil is a very large, populous region, and thus, it is hard to monitor the dynamics of its desertified areas; therefore, the present study aimed to develop a minimum set of biophysical indicators to qualify and monitor desertification in this region. This approach included sampling a pair of preserved forested areas and nearby degraded, non-forested areas which had no vegetation growth in the previous years. The study was developed in four stages: (a) pilot site selection; (b) quantification and analysis of soil and vegetation biophysical indicators; (c) biophysical indicator selection; and (d) elaboration of the minimum set of biophysical indicators and desertification levels. Of the analyzed 24 biophysical indicators, 11 were retained and subjected to factor analysis by its principal components. This yielded the minimum set of indicators used to estimate the desertification levels of the pilot sites, which consisted of four soil characteristics: Total Organic Carbon (TOC), cation exchange capacity, clay content, and magnesium content. Regressions were conducted using the SQI, and these indicators showed that the TOC had the highest coefficient of determination. In an exploratory analysis, high SQI (low desertification) showed a positive correlation with the normalized difference vegetation index (R = 0.70) and Aridity Index (R = 0.97). This methodological approach could form the basis of a dynamic monitoring system that is capable of supplying objective, quantitative, and easy to obtain information to decision-makers in NE Brazil and other dry ecosystems around the globe.

A introdução dos processos algorítmicos na atividade de curadoria de conteúdo midiático, aliada à possibilidade de publicação automatizada, têm erguido novas e importantes questões sobre o papel social do jornalismo. O chamado “jornalismo algorítmico” (LINDÉN, 2017) é um campo em constante evolução e o cálculo das suas implicações não só para a profissão, mas para toda a sociedade informatizada, ainda permanece um desafio. Neste artigo, procuraremos reunir algumas definições correntes sobre o jornalismo algorítmico e traçar um panorama das atuais relações entre informação pública e tecnologias de automação.Palavras-chave: Algoritmos. Automação. Jornalismo algorítmico.